• 专利附录
  • 专利说明
  • 权利要求
  • 类似技术
  • 同族专利
  • 引用文献
  • 法律状态
  • 优先权
    • 专利摘要:

    公开号:AT510101A2
    申请号:T13622011
    申请日:2011-09-21
    公开日:2012-01-15
    发明作者:Markus Dipl Ing Thomas；Thomas Dipl Ing Pels；Richard Dipl Ing Schneider；Bernhard Dipl Ing Dr Techn Kortschak；Carsten Dipl Ing Kaup；Kranthi Kumar Kanike；Johannes Dipl Ing Grether；Frank Dipl Ing Deitermann；Heiko Dr Braak；Tobias Dipl Ing Schaefer
    申请人:Avl List Gmbh；
    IPC主号:
    专利说明:

    < F / 0 < W9 89 299465 P.004 / 019 21/09/2011 1220 Samson & partner
    1
    DRIVING CYCLE FOR DRIVING SIMULATION
    The invention relates to a method for generating a driving cycle data set, which represents a driving cycle for a driving simulation, a method for generating a longitudinal profile and a method for testing a motor vehicle,
    In the development of motor vehicles, in particular motor vehicle drives or components thereof, driving cycles are required, which are used in purely virtual driving simulations or even in case of simulated simulations on a test bench. 10 There are legally prescribed driving cycles, for example to determine the fuel consumption of a passenger car with an internal combustion engine. However, in order to simulate different driving situations, for example city traffic or upland driving, different driving cycles are required. Conventionally, such driving cycles are generated by (real) driving off of a specific route with specially equipped vehicles which metrologically record the information required for the driving cycle during driving.
    According to a first aspect of the invention, in the method for computer-based generation of a driving cycle data set representing a driving cycle for a driving simulation of a motor vehicle, the driving cycle data set is automatically generated with a driving model from a road map by specifying a route in the road map as at least one input is used for the driving model.
    A second aspect relates to a method for generating a longitudinal profile record. This comprises at least two one-dimensional quantities, which are derived from at least a two-dimensional or three-dimensional variable of the driving cycle data set generated by the above method and related to the longitudinal direction along the route. One of these quantities is location, speed or acceleration of the vehicle in the longitudinal direction, and a further one of the variables is the vehicle braking or accelerating force in the longitudinal direction,
    Finally, a third aspect relates to a method for testing a motor vehicle, wherein the vehicle in a driving simulation on a test bench a Lftngsprofil data set generated with the above 30, is driven: Here, the vehicle is caused on the test bench on the one hand, his Driving wheels according to the size, speed or acceleration specified in the longitudinal profile; On the other hand, its drive wheels are braked or accelerated by the test bench in accordance with the force prescribed in the longitudinal profile.
    The "driving cycle data set" and the derived "longitudinal profile data record" designate one sequence of instructions for the driving simulation (ie not the driving simulation 21/09/2011 12:21)
    N °: R843 P.004 / 019 21/09/2011 1220 Samson ft Partner fAXH9 89 299465 P.005 / 019
    «♦ ·» «« · · · 2 itself).
    The "driving simulation" is, for example, a drive following the instructions of the driving cycle data record or of the longitudinal test data record 1 with a real vehicle or vehicle drive to be considered (or the component for this purpose) under scrutiny. It is thus 5 to a partial simulation (simulated is the ride, but not the vehicle or the vehicle drive or the component for this purpose).
    In other examples, the driving simulation is a full simulation in which driving with a virtual vehicle or vehicle component (or component thereof) is simulated according to the driving cycle or longitudinal profile record. In the following, optional embodiments, which are also part of the dependent claims, described in more detail.
    The road map comprises a road network with at least one road, a road in particular comprising two ends. A road may be connected via at least one node to at least one other road. If the node is located between the ends of the road, it divides the road into two road sections.
    The route is to be understood as a path in the road network with a starting point, a different destination point and at least one intervening road. Overall, start and end points are selected in the road map such that a certain number of roads (connected by knots) are arranged between them. Thus, the route includes at least one length information over 20 a distance between start point and destination point along the roads covered by the route). In addition, you can save more information on the map (see below). Here and also below, with regard to the road map and with regard to information, the term "store" is to be understood as representing the information in the road map. The road map can thus have such information directly as date or dataset. Alternatively, such information may also be contained indirectly in other data so that it can only be derived from it by an intermediate step.
    By means of the driving model, the route is virtually retraced in order to obtain information for generating the driving cycle data record. During virtual descendants, time-dependent location information and / or time-dependent speed information and / or time-dependent acceleration information, such as longitudinal and / or lateral acceleration information (in each case along the route) is (at least) generated from a location information (route) and stored in the record representing the drive cycle. The driving cycle data set thus includes, for example, a route Zdt profile, a speed-time profile, a speed-local profile, an acceleration time ·· profile and / or a height-local profile. In such a profile, the location, speed, and / or acceleration information in some embodiments is one, two, or three times. 21/09/2011 12:22
    No .: R843 P.005 / 019 21/09/2011 12:21 Samson & Partner (W + 49 89 299465 P .006 / 019 ·· **** · * 1 • | · i * * · »* * · • I t *« ··· «· * • I t ·« · · · »1 3 onal size.
    In some embodiments, the driving cycle data set is provided for a driving simulation of an electric vehicle, a hybrid vehicle, and / or an electric vehicle with a range extender, "electric vehicle" herein means a vehicle with pure electric drive and "hybrid 5 vehicle". a vehicle whose drive (when ready for operation) always comprises two drive units of different technology.
    Hybrid vehicles are therefore equipped with at least two (different) energy sources for drive energy, for example with an electric energy storage and a tank for conventional fuel (eg gasoline or diesel), as well as with corresponding different units (z, B, electric motor or, internal combustion engine with generator Here, it is important to coordinate the different energy sources and / or the respective designed drive components, for example, in terms of performance and / or ranges, "Range Extender" means a range enlargement Vorrfchtung with the electric vehicle (if required) can be additionally equipped to its To increase range. The Range 15 Extender, for example, is equipped with an internal combustion engine with an electric generator to provide additional electrical propulsion energy to the electric vehicle. Incidentally, in functional terms, the pure (and also operable as such) electric vehicle can be operated in a hybrid mode by means of the range extender (bedarflsweise, namely in the mounted state of the range extender). With regard to the road map, various embodiments are described below:
    In some embodiments, the road map includes altitude information used as a further input to the driving model. Here, in some embodiments, the road network is stored two-dimensionally in the road map and the third dimension represented by the altitude information (separately), for example, as a separate Gelfindehöhenmodetl. In other embodiments, altitude information is directly associated with the roads, the road sections, the road ends and / or the node
    In some embodiments, altitude information from a separate data source is additionally or alternatively used as a further input variable for the driving model. The separate data source is provided in addition to the road map and is for example a separate altitude map or a 30 altitude mode] I. The altitude information from the separate data source can be (the road
    Information) of the road map overlay. For a higher accuracy of the simulation, a higher spatial density of the altitude information is provided, for example, by assigning a number of altitude information along a course to it and / or by making the altitude information not fall below a certain spatial density. For example, at least every 0.5, 1, 2, 5, 10 or 50 meters of altitude and / or all I, 21/09/2011 12:22
    No .: R843 P.006 / 019 21/09/2011 12:21 Samson & Partner (FAX> 49 89 299465 P.007 / 019 t «« · »i ·» i · · * · «· I« I «I · · * * ψ I · t» · ··· · · · 4 5, 10, 50 or 100 meters along a road are provided in each case one height information.Overall, the height information is stored as an absolute size, for example in relation to the sea level, and / or as a relative size, for example as a slope.
    From the altitude information, in some embodiments, a change in the potential energy during (virtual) driving along the route is taken into account by the driving model. For example, from the Fahnnodell tensile and shear forces in uphill or downhill are derived. Accordingly, a drive cycle data set generated in this way is designed for the simulation of recuperation processes while driving along the route.
    In some embodiments, the road map includes road describing information that is used as another input to the driving model. The road-describing information includes, for example, locations of traffic lights, speed limits, curve radii, expansion state, and / or road type. Here, the state of expansion indicates, for example, information about the width of the road, the nature and / or the wear of the road surface. As road types, for example, highways, highways, main roads, minor roads, inner-15 local roads, non-local roads and / or agricultural and forest roads are distinguished. By means of such road information, the driving model selects suitable speeds for (virtual) driving along the route.
    As a further input variable for the driving model, in some embodiments traffic information is stored which is stored in the road map. The traffic information includes, for example, information about traffic, traffic obstructions, traffic incidents and / or construction sites. Incidentally, in some of these embodiments, the traffic information is stored in terms of time and / or date specific. For example, different traffic volumes on Sundays and public holidays as well as on weekdays, holiday travel and / or commuter traffic can be taken into account in the driving cycle data record. 25 The driving model! In some embodiments, it is designed for at least two driving behaviors, for example for sportive and / or energy-saving driving behavior. Accordingly, different driving cycle data bits are generated for the simulation of different driving behaviors. Incidentally, this makes it possible to take into account different driver groups with the driving model, for example different age groups. In some of these embodiments 30 different directional speeds, acceleration, braking and / or switching behavior are provided in the driving model for different driving behaviors. As a directional speed, a preferred according to the driving behavior preferred driving speed on the respective road is called, but is influenced by other factors, for example by a speed limit, traffic and / or environmental influences (see below), 35 environmental influences are in some embodiments as a further input variable of Fahrmo- 21/09/2011 12:23
    No .: R843 P.007 / 019 21/09/2011 1222 Samson £ Partner <f AX> +49 89 299465 P.008 / 019 # ··· * «* 1 ti · I f ♦ # * · ·· • 9 # · * · «· ** | For example, wind force, wind direction, precipitation, snow / ice smoothness, brightness, temperature, date and / or altitude environmental influences affect both the driver and his driving behavior, for example, slower driving in the dark or rainfall, as well as on the vehicle and the driving dynamics, such as the wind load. It is also possible to take into account additional units of the vehicle, for example windscreen wipers, lighting and / or air conditioning, which are operated in accordance with the environment and which compete with the drive power. From the date and / or time information, for example, a position of the sun and the resulting lighting conditions can be determined and their influence on the driving behavior taken into account.
    In some embodiments, information about a vehicle class is taken into account by the driving model. As vehicle classes, for example, passenger cars and trucks are distinguished or even sports cars, small cars, SUVs, vans o.ä .. Using the information about the vehicle class can be considered by the driving model, for example, with what speeds a road or route is virtually retraced, or which roads are allowed or forbidden for the respective vehicle class. In some embodiments, at least one characteristic of a particular vehicle model is considered by the driving model, for example mass, center of gravity, air resistance, Kurvenstabiütät, braking and / or acceleration performance of the particular vehicle model.
    Incidentally, while the driving cycle data set determines the driving dynamics during simulation (within certain limits), on the other hand, certain driving maneuvers or driving behaviors are only possible or impossible with certain vehicle models and / or vehicle classes. In order to reflect this in the driving cycle data set, in some embodiments at least one driving-dynamically relevant variable (of the vehicle) is taken into account by the driving model. As a result, the driving cycle data set can be adapted to different vehicle models and / or vehicle classes. For example, dimensions, center of gravity, cornering stability, braking and / or acceleration power of the vehicle and / or the operation of additional units such as air conditioning are considered as driving dynamics relevant variables , Seat and / or window heating considered. For a simplified generation of the driving cycle dataset, in some embodiments the route is automatically determined for predetermined starting and destination points by means of the road map. For this purpose, starting point and destination point are defined in the road map and a route is automatically calculated as connecting these points along roads connected by nodes. In addition, in some of these embodiments, at least one intermediate destination is considered, which is finally detected before the route.
    In some of these embodiments, when determining the route, certain types of roads (see above) are preferred or avoided over other types of roads. In this case, it is accepted that the route thus determined is longer than an alternative route or a longer route. 21/09/2011 12:23
    No .: R843 P.008 / 019 21/09/2011 12:22 Samson £ Partner (FAX) +49 89 299465 P.009 / 019 ·· t · »· · ·« · f ·· * · · * ··· »* * 6 driving time is needed, but a more favorable ratio of preferred or avoidable roads to non-preferred or unavoidable roads is achieved.
    In some of these embodiments, vehicle-specific criteria are taken into account in the determination of the route, in particular restrictions of headroom and / or restrictions for cars, trucks and / or two-wheelers. In this way, unrealistic routes can be automatically filtered out.
    The invention simplifies the creation of driving cycle data records, which map the real conditions in detail. It also facilitates the creation of a large number of different variants of driving cycle data sets, which differ, for example, from geographical, climatic, traffic-related, vehicle-specific and / or various factory behavior-related influences. This is particularly useful for the development of hybrid vehicles, since these are complex in terms of hybrid control (ζ, Β, tuning and dimensioning of different drive components, storage strategy) and therefore a relatively large "simulation breadth" in development is advantageous. The same applies to pure electric vehicles or for the development of appropriate range extender.
    According to the second aspect of the invention, in some embodiments, the longitudinal profile record is generated from the driving cycle record, which also (but in another form) reflects the driving cycle. The "longitudinal profile" designates a data set with one-dimensional variables, namely at least location, speed or acceleration information and a force information representing a (total) load and the simulation of load torques that occur during a real journey to a real one Vehicle would be possible. For this purpose, (if appropriate) multidimensional variables such as location, speed and / or acceleration data of the drive cycle data set are each referenced to a one-dimensional location or speed indication, e.g. as a function of time (namely along the longitudinal direction of the route underlying the driving cycle) as well as the total force acting on the vehicle, also, for example, as a function of time or distance. The Längsprofll data set thus formed is an input to a test rig, with which a partial simulation of the vehicle is performed: the drive of the (real) vehicle operates so that the wheel speed of the vehicle of the (forward direction reduced) local or speed specification of the driving cycle corresponds without the vehicle actually moving. Thus, in this type of partial simulation, the forces caused by the vehicle's travel are absent (e.g., inertial forces at vehicle acceleration, weight force when traveling on inclined strokes, air resistance, rolling resistance, and possibly braking forces at cornering). These "missing" forces in the test bench due to FahrzeugetilIstands be generated with the roller test bench by a suitable braking and, if necessary, also drive torque as a function of time or the distance traveled. 35 This braking and possibly also drive torque is released from the roller (s) of the test bench * 21/09/2011 12:24
    No .: R843 P.009 / 019 (FAXHS 89 299465 P .010 / 019 21/09/2011 12:23 Samson & Partners
    • * * * * * * * * * * *
    The mapping of the driving cycle on the longitudinal profile is such that this (one-dimensional) braking and driving torque corresponds to the time or the braking and driving torque with which the drive of the Vehicle would be acted upon in real driving according to the driving cycle. Thus, in the bench test corresponding to the longitudinal profile, the vehicle is driven at the one-dimensional speed (relative to the bench rolls) as a function of the time corresponding to the drive cycle, and at the drive wheels it experiences the braking or driving torque that it has would be experienced real driving according to the driving cycle. The mapping of the drive cycle to the longitudinal profile thus takes into account those parameters of driving dynamics that are not real due to the simulation of the computer (i.e., the vehicle stall) and provides the prescription of the torques to be applied with the test stand rollers to effectively model the vehicle dynamics to the vehicle dynamics.
    Incidentally, in some embodiments, a spatial, velocity, acceleration * or force information is converted, for example by means of differentiation, integration or a physical law such as the law of inertia. For example, a (time-dependent) speed variable of the longitudinal profile data set is calculated from (time-dependent) 15 location information of the drive cycle data record
    In some embodiments, the at least two one-dimensional sizes of the longitudinal profile record are time-dependent quantities. The longitudinal profile record (and / or the drive cycle data set) is for example a sequence of values associated with approximately successive constant time intervals. stored to represent the time dependency, Thus, each follower can assign a specific time information. Accordingly, (later) the instructions corresponding to the individual follow-up instructions in the test stand in the driving simulation can be successively converted according to the duration of the time intervals. In some embodiments, the two one-dimensional variables are linked to a time information vcr-25, which is likewise stored in the data record, for example as a triple of a speed, a force and a time stamp.
    The force information reflects a load acting on a real vehicle or occurring during real driving. The force information, in some embodiments, accounts for one or more of the following aspects with respect to different loads (optionally adding the contributions of different loads, in particular to a longitudinal force, i.e., longitudinal force):
    By means of the mass of the (tested) motor vehicle, the load (force) is determined during acceleration in the direction of travel, with the second Newton's law "force mass * acceleration". In addition, the mass of the vehicle flows into the determination of the vehicle accelerating component of the weight force on downhill slopes (according to the 35 height information) along the route, corresponding to "force sin (angle of longitudinal force). 21/09/2011 12: 24
    No.: R843 P. 010/019 21/09/2011 12:23 Samson &amp; Partner &lt; FAXM9 89 296465 P.011 / 019
    8 direction to the horizontal) * mass * gravitational acceleration * '.
    From the magnitude of the three-dimensional velocity, the load is modeled based on the air resistance of the vehicle (which generally depends on the speed approximately quadratically). Similarly, from the magnitude of the three-dimensional velocity, the rolling resistance is modeled (which is generally less than quadratic in speed). In some embodiments of the longitudinal profile creation is also taken into account that the Rollwi. The resistance increases during cornering due to the lateral acceleration associated with the tire deformation.
    According to the third aspect of the invention, in the method for testing the motor vehicle 10, the motor vehicle (or the vehicle drive or a component thereof) is driven in a driving simulation, in accordance with the longitudinal profile determined from the driving cycle. In some embodiments, the conversion of the Fahrzyklus5 in the longitudinal profile is carried out in advance in a separate step. In other embodiments, however, the control computer of the test rig is equipped and programmed so that it carries out the computational conversion of the driving cycle to the longitudinal profile itself, e.g. 15 time before the actual test drive or even during their course. In the case of pre-implementation, the longitudinal profile thus forms the input values for the test bench, while in the case of implementation in the control computer of the test bench it appears as if it formed the drive cycle data record. In fact, in both cases, the longitudinal profile is the same. Record the actuators of the test bench (ie, for example, the accelerator pedal operation and the vehicle opposite to set-20 zende load) controls, regardless of whether the longitudinal profile in a separate step in advance or only in the Prttft-status control unit from the driving cycle record is calculated.
    Regardless of the fact that vehicle class or vehicle model-specific properties have already been taken into account in the generation of the drive cycle data record, at least the mass and the air resistance of the vehicle to be tested are taken into account in the generation of the longitudinal profile from the drive cycle data record.
    An embodiment of the method will be described with reference to the following drawings. 1 shows a schematic representation of the method for the computer-based generation of a
    Driving cycle data set, which represents a driving cycle for a driving simulation.
    The following embodiment shows the method for generating the Fehrzyklus data set representing a driving cycle for the driving simulation of a hybrid vehicle. Further exemplary embodiments differ in that the driving cycle data set for a pure electric 21/09/2011 12:25
    No .: R843 P.011 / 019 21/09/2011 12:24 Samson &amp; Partner &lt; FAX) +49 89 299465 P .012 / 019
    9 electric vehicle or an electric vehicle with a range extender is generated.
    The driving cycle data set 1 is automatically generated according to FIG. 1 with the driving model 2 from the road map 3. For this purpose, m 4 a route in the road network 6 of the road map 3 is generated and used as an input to the driving model 2. In the following, in this order the road network 6, the generation of the route, the road map 3 and finally the generation of the driving cycle data set 1 will be described. These and the operations described below are determined by a computer program stored in memory and, unless explicitly stated otherwise, are executed by a computer programmed to execute the computer program. The information mentioned below is stored at least in the generation of the 10 driving cycle data set 1 in the computer.
    To determine the route, the starting point and the destination point as well as, if necessary, intermediate destinations are set manually in FIG. 4. In addition, the vehicle class to be simulated, for example a passenger car, as well as further route options, for example an optimization according to the shortest route or alternatively after the shortest travel time and / or the preferred use of autobahns, are also set manually. In compliance with these requirements, the route is automatically determined within half of the road network 6. Incidentally, vehicle-specific criteria are also taken into account in this case, for example passage restrictions for the selected vehicle.
    The road network 6 of the road map 3 in this embodiment comprises a two-dimensional map of a road traffic network of a certain geographical area, where roads 20 are stored in the road map 3 as (slender) polygons, so that also (approximately) information about Kurvenradfen indirectly contained in the road map 3 , Inter-street links are represented by nodes. The spatial (two-dimensional) position of the roads, their individual course and the location of the nodes are coded by geo-coordinates.
    In addition to the road network 6, a terrain elevation model 9 of the area covered by the road network 6 is stored in the road map 3. On the terrain elevation model 9, the elevation of the earth's surface above sea level can be determined (at least within the area covered by the road network 6) Area). In other examples, terrain elevation is modeled as separate from the roadmap 3.
    Also, the road map includes 3 road information sites 10, including locations of traffic lights, road speed limits, and road typing, for example, on highways, single or multi-lane roads, inner and outer roads. These road information 10 are assigned as records to the respective roads of the road network 6.
    The driving cycle data set 1 is generated, as mentioned above, with the driving model 2 from the road map 3. For this purpose, the driving model 2 travels virtually along the route from the starting point to the destination point, wherein the route represents an input variable of the driving model 2. This virtual driving, which he · 21/09/2011 12:25
    No .: R843 P.012 / 019 21/09/2011 12:24 Samson 4 Partner (FAXH98929M65 P .013 / 019 1
    10
    Generation of the driving cycle data set 1 is to be distinguished from the above-mentioned Fahrsimuiation the vehicle on the test bench, for the driving cycle data set 1 is ultimately provided. For the virtual driving along the route in the driving model 2 different driving behaviors 12 are implemented, whereby the braking and acceleration behavior, and the 6 Schaltverhahen (in vehicles with manual transmission) is taken into account for different types of drivers. For example, driving behaviors 12 of a sporty driver who is relatively fast, slows down, shifts late and drives at maximum permissible speed, and uses an energy-efficient driver who slows down a little, uses longer coast-downs, gently accelerates, shifts early, and about 0% -90 % of the maximum permissible speed, but a maximum of about 130 km / h strives, provided in the driving model 2.
    The (slender) polygonal representation of the road network 6 allows the driving model 2 to determine on the one hand actual distances exactly. On the other hand, a realistic speed profile along the route is determined for the currently selected driving behavior 12 from the curve of the road guidance, wherein additionally the road information 10 and traffic information 11 are taken into account as further input variables. In an alternative embodiment, the roads are implemented as (straight-line) routes between the nodes in the road network 6. Information about the respective curve of the roads are stored as separate data in the road map 3.
    From the elevation model 9 of the road map 3 as a further input variable determines the driving model 20 2 by means of geopositions along the route height changes in virtual driving and stores it as a height profile in addition to the speed profile in the driving cycle data set 1. In addition, taking into account the driving dynamics relevant Sizes derived from the height profile shear and traction forces on inclines and inclines along the route.
    Ala further input variables are used by the driving model 2 driving dynamics relevant variables 13 ver-25 to the virtual driving along the route for the selected vehicle, ie for a specific
    Vehicle Mode]], as realistically as possible. Here are, for example, the mass, the air resistance, maximum allowable lateral acceleration forces and maximum braking and acceleration performance of the vehicle available. These variables influence, for example, the maximum acceleration and / or speed of the vehicle and are accordingly taken into account in the generation of the driving cycle data set 1, in particular the speed profile.
    As a further input traffic information 11 from the driving model 2 are taken into account. The traffic information 11 includes, for example, empirical data on the respective traffic volumes of the respective roads as a function of the time of day and taking account of working days and Sundays and public holidays. The traffic information 11 are assigned as records to the respective roads of the road network 6. However, not all roads have such traffic in · 21/09/2011 12:26
    No .: R843 P.013 / 019 21/09/2011 1225 Samson &amp; Partners (FAXM9892B9465 P.014 / 019 1 11 format) 11, so that, if necessary, existing traffic information 11 is used for roads of the same street type in close proximity to the surroundings I These include, for example, wind force and wind direction, precipitation and / or snow and ice smoothness Such environmental influences 14 on the one hand affect the vehicle itself, for example by applying additional drive power to overcome the wind resistance It also affects the driver, who, for example, reduces the driving speed in the event of heavy rainfall.Accordingly, the environmental influences 14 are used as correction terms with regard to the driving behavior patterns 12. Finally, it is also possible to do so a different driving cycle · generate data sets 1, for example for day and night driving or for different weather conditions, for example for summer and winter rides.
    The drive cycle data set 1 generated by the drive model 2 (taking into account the aforementioned input variables) is stored as a data set which includes a speed-time profile 15. In this profile, the speed data is stored as a three-dimensional variable or alternatively creates a location-time profile and / or a acceleration-time profile. In some embodiments, the location, speed or. Acceleration data of the respective drive cycle data records are stored as one-, two- or three-dimensional information. Incidentally, in another embodiment, the longitudinal profile record is generated from the ferry cycle record. This in turn is done by a suitably equipped computer, namely a computer with a computer program stored in a memory of a computer and, when executed, causing the computer to perform the described method. For this purpose, multidimensional data of the driving cycle data set, such as location, speed or acceleration data, are used to calculate time-dependent, one-dimensional longitudinal speeds as well as time-dependent, one-dimensional longitudinal forces (load), the values of which relate to the longitudinal directions along the route , In this example, the longitudinal profile data record consists of a sequence of value pairs of one longitudinal velocity and one longitudinal force each. Here, the sequence represents a time sequence in even magazines. In further embodiments, the motor vehicle, the vehicle drive (or the
    Component) on the test bench by driving it in a driving simulation according to the longitudinal profile calculated from the driving cycle. This is represented by a longitudinal profile record in various variants of embodiments. This is a sequence of instructions for the driving simulation so that the (respective) data set is an input parameter for the test bench. 21/09/2011 12 26
    No .: R843 P.014 / 019 21/09/2011 12:25 Samson &amp; Partner (FAXHS 89 299465 P.015 / 019 ······ ··· • »· ·« · * * · · · *
    I * * * t »» i * 4 »« «« * o * * * 12
    On the one hand, the vehicle on the test bench is caused, on the one hand, to drive its driving wheels according to the longitudinal profile of e.g. driving location, speed or acceleration as a function of time or distance; On the other hand, its driving wheels are measured from the test bench according to the longitudinal profile, e.g. also braked or accelerated as a function of time or distance before given force. The drive of the (real) vehicle then operates SO, so that the wheel speed of the vehicle corresponds to the location or speed preset of the drive cycle (reduced to the forward direction) without the vehicle actually moving. Thus, in this type of sub-simulation, the forces caused by the vehicle's travel are absent (e.g., inertial forces in vehicle acceleration, weight when driving on an incline, 10 aerodynamic drag, rolling resistance, and possibly cornering braking forces). These "missing" in the test bench Prüfüng due to the vehicle standstill forces are generated with the roller test bench by a suitable braking and, if necessary, also drive torque as a function of time or the distance traveled. This braking and possibly also drive torque is applied by the one or more rollers of the test stand, act on the drive wheels of the vehicle to be tested. In the test bench according to the longitudinal profile, therefore, the vehicle is driven at the one-dimensional speed (relative to the test roller) as a function of the time corresponding to the driving cycle, and at the drive wheels it experiences the braking or driving torque that it would be experienced in real driving according to the driving cycle. The illustration of the driving cycle on the Längsprofi) thus takes into account those variables of the vehicle dynamics that do not actually occur due to the partial simulation 20 (d, h, the vehicle standstill), and provides the specification of the applied with the test bench roles moments to the vehicle drive these driving dynamics sizes in a sense pretend. 21/09/2011 12:27
    No.; R843 P.015 / 019
    权利要求:
    Claims (12)
    [1]
    1226 Samson &amp; Partner m * 49 89 299465 P.016 / 019 13 PATENT CLAIMS 1. A method for computer-based generation of a drive cycle data set (1), which represents a drive cycle for a driving simulation of a motor vehicle, in particular a vehicle with hybrid drive, wherein the drive cycle Record (1) is automatically generated with a Fahnnodell (2) from a road map (3) by using a route in the road map (3) as at least one input variable for the Fahnnodell (2).
    [2]
    2. The method according to claim 1, wherein the road map (3) altitude information (9), which are used as a further input to the driving model (2).
    [3]
    3. The method according to claim 1 or 2, wherein Höheninformattonen from a separate data source is used as another input to the driving model (2).
    [4]
    4. Method according to one of the preceding claims, wherein the road map (3) comprises road-descriptive information (10) which is used as a further input variable for the driving model (2), in particular road-describing information (10) about traffic lights, speed limits, curve radii, Expansion state and / or road type.
    [5]
    5. The method according to any one of the preceding claims, wherein the road map (3), in particular clock time and / or date-specific, Verkehrsinfbrmationen (11), which are used as a further input variable for the driving model (2).
    [6]
    6. The method according to any one of the preceding claims, wherein the Fahnnodell (2) for at least two, in particular sporty and / or energy-saving, driving behaviors (12) is designed, in particular by the driving model (2) directing speeds and / or accelerating, Braking and / or switching behavior taken into account.
    [7]
    7. Method according to one of the preceding claims, wherein at least one environmental influence (14) is taken into account by the driving model (2), in particular wind strength, wind direction, precipitation, snow / ice glare, brightness, temperature, date and / or time information. S. Method according to one of the preceding claims, wherein at least one vehicle-dynamically relevant variable (13) of the vehicle is taken into account by the driving model (2), in particular 21/09/2011 12:27 No .: R843 P.016 / 019 21 / 09/2011 12:26 Samson &amp; Partner (FAXH9 89 299465 P.017 / 019 ·· * ··· * * ·· I t · * · »- ·« · * f 4 I »» * »» - * 4 * · · · · »I * Particular mass, center of gravity, air resistance, curves stability, braking and / or acceleration performance of the vehicle and / or the operation of additional units such as air conditioning, seat and / or window heating,
    [8]
    9. Method according to one of the preceding claims, wherein the route is automatically determined for a predetermined starting point and destination point by means of the road map (3), in particular an intermediate destination being taken into account,
    [9]
    10, A method according to claim 8, wherein in the determination of the route certain types of roads, in particular 10 highways and / or highways, preferred or avoided.
    [10]
    11, A method according to claim 8 or 9, wherein in the determination of the route vehicle-specific criteria are taken into account, in particular restrictions on passage heights and / or passage restrictions for cars, trucks and / or two-wheelers. 15
    [11]
    12. A method for producing a longitudinal profile data set comprising at least two one-dimensional variables, wherein the sizes of at least a two- or three-dimensional size of the driving cycle data set (1) generated according to one of claims 1 to U are derived and along the longitudinal direction the route, and wherein one of the variables location, 20 speed or acceleration of the vehicle in the longitudinal direction and a further of the variables are a vehicle braking or accelerating force in the longitudinal direction.
    [12]
    13. A method for testing a motor vehicle, wherein the vehicle in a driving simulation on a test bench a Längsprofii data set is traversed according to claim 12, 25 causes the vehicle on the test stand on the one hand to his driving wheels accordingly in the longitudinal profile specified Size location, speed or acceleration to drive, and on the other hand its drive wheels are braked or accelerated by the test bench according to the predetermined force in the longitudinal profile. 21/09/2011 12:28 No .: R843 P.017 / 019
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    法律状态:
    优先权:
    申请号 | 申请日 | 专利标题
    AT13622011A|AT510101B1|2011-09-21|2011-09-21|Method for the computer-based generation of a driving cycle data record and a longitudinal profile data record and method for testing a motor vehicle|AT13622011A| AT510101B1|2011-09-21|2011-09-21|Method for the computer-based generation of a driving cycle data record and a longitudinal profile data record and method for testing a motor vehicle|
    DE201210018359| DE102012018359A1|2011-09-21|2012-09-17|DRIVING CYCLE FOR DRIVING SIMULATION|
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